Towards In-Network Security for Smart Homes

Serror, Martin; Henze, Martin; Hack, Sacha; Schuba, Marko; Wehrle, Klaus

doi:10.1145/3230833.3232802

Cited by 27 publications

(8 citation statements)

References 20 publications

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“…With SDN, changes to network separation can be configured quickly, e.g., to counter cyber attacks. Likewise, SDN can be used to enforce network compliant behavior, e.g., specified using communication rules by the operator of the communication network [ 109 , 110 ]. Dong et al [ 111 ] and White et al [ 112 ] provide more information on the opportunities and challenges of using SDN for smart grid resilience.…”

Section: Providing Cybersecurity For Interconnected Power Gridsmentioning

confidence: 99%

Cybersecurity in Power Grids: Challenges and Opportunities

Krause

Ernst

Klaer

et al. 2021

Sensors

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Increasing volatilities within power transmission and distribution force power grid operators to amplify their use of communication infrastructure to monitor and control their grid. The resulting increase in communication creates a larger attack surface for malicious actors. Indeed, cyber attacks on power grids have already succeeded in causing temporary, large-scale blackouts in the recent past. In this paper, we analyze the communication infrastructure of power grids to derive resulting fundamental challenges of power grids with respect to cybersecurity. Based on these challenges, we identify a broad set of resulting attack vectors and attack scenarios that threaten the security of power grids. To address these challenges, we propose to rely on a defense-in-depth strategy, which encompasses measures for (i) device and application security, (ii) network security, and (iii) physical security, as well as (iv) policies, procedures, and awareness. For each of these categories, we distill and discuss a comprehensive set of state-of-the art approaches, as well as identify further opportunities to strengthen cybersecurity in interconnected power grids.

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Section: Providing Cybersecurity For Interconnected Power Gridsmentioning

confidence: 99%

Cybersecurity in Power Grids: Challenges and Opportunities

Krause

Ernst

Klaer

et al. 2021

Sensors

Self Cite

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“…The IoT botnet infection attempts typically involve port scanning, vulnerability exploitation and transfer and execution of bot malware. The detection may be performed by a network intrusion detection system (NIDS) [26] at the network perimeter, or by a host intrusion detection system (HIDS) [27] or antivirus operating on the device. A NIDS typically monitors the network traffic while an antivirus or a HIDS inspect system changes and program execution.…”

Section: B Iot Botnet Detectionmentioning

confidence: 99%

An Automated and Comprehensive Framework for IoT Botnet Detection and Analysis (IoT-BDA)

Trajanovski¹,

Zhang

2021

IEEE Access

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The proliferation of insecure Internet-connected devices gave rise to the IoT botnets which can grow very large rapidly and may perform high-impact cyber-attacks. The related studies for tackling IoT botnets are concerned with either capturing or analyzing IoT botnet samples, using honeypots and sandboxes, respectively. The lack of integration between the two implies that the samples captured by the honeypots must be manually submitted for analysis in sandboxes, introducing a delay during which a botnet may change its operation. Furthermore, the effectiveness of the proposed sandboxes is limited by the potential use of anti-analysis techniques and the inability to identify features for effective detection and identification of IoT botnets. In this paper, we propose and evaluate a novel framework, the IoT-BDA framework, for automated capturing, analysis, identification, and reporting of IoT botnets. The framework consists of honeypots integrated with a novel sandbox that supports a wider range of hardware and software configurations, and can identify indicators of compromise and attack, along with anti-analysis, persistence, and anti-forensics techniques. These features can make botnet detection and analysis, and infection remedy more effective. The framework reports the findings to a blacklist and abuse service to facilitate botnet suspension. The paper also describes the discovered anti-honeypot techniques and the measures applied to reduce the risk of honeypot detection. Over the period of seven months, the framework captured, analyzed, and reported 4077 unique IoT botnet samples. The analysis results show that some IoT botnets used antianalysis, persistence, and anti-forensics techniques typically seen in traditional botnets.

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“…Hence, in a simple environment, advanced users [75] can customise the pre-defined policies [172,73], such as MUD [101], to meet their security and privacy requirements. Smart spaces also include other security services such as IDS [161,134,40,116]. Thus, there are three main security components for smart spaces: user input, pre-defined IoT policies, and network security middleboxes, which need to be incorporated when designing smart space security system.…”

Section: Motivationmentioning

confidence: 99%

Fine-grained Access Control for Internet of Things Smart Spaces Driven by User Inputs

Al-Shaboti¹

2021

Preprint

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The increasing use of Internet of Things (IoT) devices raises security and privacy concerns. In smart spaces, multiple IoT devices are simultaneously used to fulfil user activity functions. However, these devices exhibit several security vulnerabilities that can compromise smart space security and privacy. The ability of fine-grained control network access in IoT devices and application messages can significantly reduce the risk resulting from the exploitation of IoT vulnerabilities due to unauthorised access, thereby improving smart space security. A well-recognised approach in the literature for IoT access control is to use pre-defined access policies to allow the necessary connections for a device to function correctly. However, these policies allow access to all device functions (i.e. coarse-grained access) including those functions that are not used by any user activity. The overall goal of this thesis is to develop an access control framework and techniques to achieve fine-grained access policies by using user inputs. The user inputs will be utilised to select devices to fulfil user activities aiming to build an access policy from the minimum access required for each device function. In this thesis, the use of user inputs to meet user security and privacy requirements in single- and multi-user smart spaces is studied. The main contributions are as follows: first, an access control framework that enables users to tailor IoT device policies to meet their security and privacy requirements is proposed. Validation results of the framework show the effectiveness of integrating user access rules into the existing security countermeasures (i.e. pre-defined policies and intrusion detection systems – IDS) to enforce user security and privacy. Second, the problem of selecting preferable devices to fulfil user activity functions is formulated as an optimisation problem. The optimisation problem is then solved by local and global optimisation searching algorithms that are guided by a developed user preference quantified model. The results show that global optimisation search algorithms such as Genetic Algorithm (GA) find the solution more effectively and efficiently than local search algorithms such as simulated annealing and hill-climbing. Third, sharing access control for multi-user smart spaces is proposed. Traditional access control that considers a single user is not suitable for multi-user smart spaces, where users share their IoT devices. The sharing between multiple users poses challenges different than in single-user access control. For example, users may abuse using shared devices and use vulnerable ones. This thesis addresses these two challenges through two contributions. First, it proposes a novel sharing policy language that enables users to precisely define their sharing policy. Second, this thesis formulates the sharing policies as constraints in the context of an optimisation problem with the objective function that maximises the use of secure devices. Results show that the IoT sharing issue can naturally be translated into an integer linear programming (ILP) problem and effectively solved using off-the-shelf ILP solvers. Fourth, this thesis explores the feasibility and practicality of the fine-grained access policy enforcement through a smart home case study. A case study is built using a hub-based architecture that uses Web of Things (WoT) technology. WoT provides a device semantic description that includes device functions with the corresponding Uniform Resource Identifier (URI) which is used to build access control policies. The case study results show that policy enforcement can be effectively achieved by directing network traffic through a device proxy for each IoT device to enforce application access control without introducing statistically significant overhead on the user activity running time. In summary, this thesis studies the use of user inputs to derive fine-grained access control in smart spaces. For a single-user access control system, this thesis considers using manual rules and user preferences in small and dense smart spaces, respectively. For a multi-user access control system, this thesis proposes a secure sharing system supported by a sharing policy language to share and use IoT devices securely. For each scenario analysed, user input is utilised to derive fine-grained access policies. Enforcement of these policies has been explored by implementing a smart space case study using WoT technology. The overall results show that user preferences and sharing policies can be used to derive fine-grained access policies that are transparent to users and meet their security and privacy requirements.

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Towards In-Network Security for Smart Homes

Cited by 27 publications

References 20 publications

Cybersecurity in Power Grids: Challenges and Opportunities

Cybersecurity in Power Grids: Challenges and Opportunities

An Automated and Comprehensive Framework for IoT Botnet Detection and Analysis (IoT-BDA)

Fine-grained Access Control for Internet of Things Smart Spaces Driven by User Inputs

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